Nonlinear estimation for condition monitoring of advanced gas-cooled nuclear reactor cores

As the Advanced Gas-cooled Reactor (AGR) nuclear power stations are ageing, the nuclear core composed by graphite bricks can distort. The direct measurement of the core condition is costly and time-consuming, hence, alternative methods have been developed to provide the necessary information about the core condition. This thesis presents a model-based technique for condition monitoring of AGRs cores using measurements obtained during routine core refuelling process. It has been demonstrated that Fuel Grab Load Trace (FGLT) data gathered during refuelling operations provides, through the magnitude of its friction component, information relating to the condition of the graphite bricks. Therefore, the condition monitoring of an AGR leads to the estimation of the friction force resulting from the interaction of the fuel assembly and the core channel. To this end the main objective of this work is to investigate estimation techniques that are needed in industrial applications and in particular can be used in the refuelling filtering problem. As a result of this study, a novel LPV estimator and robust estimator have been designed and implemented. A model for the refuelling system was initially developed from the first principles of the process. Then its fuel assembly dynamics subsystem was identified to be used in a model based filtering application. Finally a H robust estimator was employed to estimate the friction force to be used for the core condition analysis.

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Thumbnail	Titolo	Data caricata	Visibilità	Azioni
	PDF of thesis T13173	2021-07-02	Pubblico	Scaricare